First-order Lag Research Articles

The Impact of Policy Quantification on Rural Spatial Development in Suburbs: A Case Study of Dalian’s Main Urban Area

Under China’s rural revitalization strategy, peri-urban villages function as pivotal nodes in urban–rural integration. Existing policy research predominantly emphasizes macro-level land and industrial policies, neglecting their spatial development effects on peri-urban villages. This study addresses the gap by constructing a policy quantification framework and employing a Vector Autoregression (VAR) model to analyze policy impacts on rural spatial development, focusing on peri-urban villages in Dalian’s main districts from 2004 to 2023. The results indicate a fluctuating yet upward trend in policy effectiveness. Initial supply-side policies prioritized infrastructure development, whereas subsequent demand-side policies significantly enhanced living conditions, underscoring the necessity of adaptive policy strategies. The rural revitalization construction index exhibited notable spatial heterogeneity, evolving from clusters near industrial zones to expansion into areas like the Jinzhou District, aligned with urban growth patterns. Granger causality analysis confirmed the strong influence of policy interventions, with the first-order lag VAR model offering reliable predictions of short- and long-term policy effects. Initially, the construction index was entirely self-driven (100%), but its reliance on self-influence waned to 69.8% over time, highlighting a transition toward greater policy-driven development.

Proportional-Navigation-Based All-Aspect Approach Against Nonmaneuvering Target Using Phase-Plane Trajectory Shaping

Approaching a target from a desired heading is crucial for various modern applications. Existing literature mostly addresses terminal angle-constrained guidance for stationary targets, which also includes strategies for achieving the entire angular spectrum (all-aspect approach). However, existing strategies against moving targets can achieve only a restricted set of terminal angles. To this end, this paper presents a proportional-navigation-based multiphase guidance strategy against a nonmaneuvering target, moving at a lower speed than the pursuer, with any desired terminal angle in 2-D, by shaping the trajectory on an angular phase plane. First, a generalized version of the two-phase guidance scheme is presented for achieving terminal angles in one half-space. This is subsequently extended to attaining any desired terminal angle in the other half-space by using an additional phase for line-of-sight rotation reversal. By shaping the angular phase-plane trajectory, the pursuer’s field-of-view constraint is also seamlessly incorporated in the guidance formulation. Further, an all-aspect approach in a 3-D environment is achieved by splitting the entire 3-D engagement into two planar engagement phases and employing the developed planar guidance on each engagement plane. The performance of the developed guidance strategies is validated through extensive numerical simulations considering first-order lag and lateral acceleration limits.

Effects of major air pollutants on cognitive function in middle-aged and elderly adults: Panel data evidence from China Health and Retirement Longitudinal Study.

Although numerous studies have discussed about the impact of air pollution on cognitive function, a consensus has yet to be reached, necessitating further exploration of their relationship. The aim of this study is to reveal the effects of major air pollutants on cognitive function in Chinese middle-aged and older adults, while considering the lagged effects of pollution. Panel data were constructed by integrating the air pollutants concentration (particulate matter diameter ≤1 µm (μm) (PM1), PM2.5, PM10, nitrogen dioxide (NO2), and ozone (O3)) among 28 provinces in China and the personal characteristics from China Health and Retirement Longitudinal Study participants during the period of 2011-2015. To explore the effects of single pollutants and their interactions on cognitive function, panel linear regression using ordinary least squares method was employed, and first-order lag effects (two-year interval) of air pollution were introduced into the models. Our study revealed that, after adjusting for confounding factors, higher levels of particulate matter (PM1, coefficient (Coef.) = -0.093, P = 0.001; PM2.5, Coef. = -0.051, P = 0.001; PM10, Coef. = -0.030, P = 0.001) and NO2 (Coef. = -0.094, P = 0.006) were associated with lower cognitive function scores among the participants. Moreover, the interaction between the five major pollutants exhibited a negative effect on cognitive function(Coef. = -2.89, P = 0.004). PM1, PM2.5, PM10 have detrimental effects on the cognitive function of middle-aged and elderly adults in China, where increasing particle diameter correlates with a less negative impacts, providing theoretical underpinnings for the formulation of environmental protection policies.

A Model-Informed Drug Development Approach to Design a Phase 3 Trial of Teverelix Drug Product in Advanced Prostate Cancer Patients with Increased Cardiovascular Risk.

Teverelix drug product (DP) is a parenteral gonadotropin-releasing hormone (GnRH) antagonist that has been successfully tested in phase 2 trials for hormone-sensitive advanced prostate cancer (APC) and benign prostatic hyperplasia (BPH). In previous APC trials, teverelix DP was administered as intramuscular (IM) and subcutaneous (SC) injections, using a loading dose and (in a single trial) a maintenance dose. Our objective was to derive an optimal dosing regimen for phase 3 clinical development, using a pharmacometrics modeling approach. Data from 9 phase 2 studies (229 patients) was utilized to develop a population pharmacokinetic (PK) model that described the concentration profile accommodating both IM and SC routes of administration. A 2-compartment model with sequential first-order absorption (slow and fast) and lag times best described the PK profiles of teverelix following SC and IM administration. An indirect response model with inhibition of production rate was fit to describe testosterone (T) concentrations based on physiological relevance. The final population PK-pharmacodynamic model was used to conduct simulations of various candidate dosing regimens to select the optimal dosing regimen to achieve clinical castration (T<0.5ng/mL by day 28) and to sustain clinical castration for 26 weeks. Model simulation showed that a loading dose of 360mg SC and 180mg IM with a maintenance dose of 360mg SC 6-weekly (Q6W) starting at day 28 can achieve a ≥95% castration rate up to 52 weeks. This dose regimen was selected for phase 3 clinical development, which includes cardiovascular safety assessment in comparison to a GnRH agonist.

Does environmental investment improve corporate productivity? Evidence from Chinese listed firms

This paper analyses the impact mechanisms of environmental investment on the productivity of listed firms in China. The empirical results show that, first of all, environmental investment has a significant negative impact on the productivity of listed firms, which confirms that listed firms have a typical compliance cost effect. Moreover, listed enterprises with low productivity and high productivity are less negatively affected by environmental investment than are listed enterprises with moderate productivity. Secondly, the first-order lag term of environmental investment has a significant inhibitory effect on the productivity of listed companies in the eastern region, but has no significant impact on the productivity of listed companies in the central and western regions. Finally, the increase in environmental investment has a great influence on the productivity of listed firms in heavily polluting industries, but it has no obvious influence on non-heavily polluting industries.

Experimental and Numerical Evaluations of Dynamic Transfer Matrix for a Three-Dimensional Centrifugal Impeller Based on Unsteady Energy Conservation

Abstract Under unsteady operating conditions in turbomachinery, the performance is unable to respond rapidly enough to follow characteristic curves for the steady condition. To design a reliable turbomachinery under unexpected unsteady conditions, we evaluated the dynamic transfer matrix of a three-dimensional centrifugal impeller. The working fluid is incompressible air. To make the current results more applicable in a broader sense such as pumps, all parameters and results were normalized. The experimental results showed a more significant negative slope in the unsteady performance curve compared to that in the steady performance curve. This was mainly caused by the phase delay of the pressure rise to the pulsating flowrate. We clarified the changes in gain and phase delay under unsteady conditions by conducting numerical simulations. The numerical results showed that the unsteady pressure rise was primarily generated by inertia and power terms in the unsteady energy conservation equation. The power term was predominantly influenced by the angular momentum flowrate difference and the change rate of angular momentum. Each term was quantitatively evaluated, and its contribution to the unsteady pressure rise was discussed. Within the range of frequencies tested in this study, the transfer matrix for the three-dimensional centrifugal impeller could be effectively approximated through a first-order lag approximation considering a series-connected derivative system. We believe that our findings can be extended to centrifugal pumps when disregarding the compressibility effects such as cavitation.

Pharmacokinetic Modeling of Bepotastine for Determination of Optimal Dosage Regimen in Pediatric Patients with Allergic Rhinitis or Urticaria.

Bepotastine, a second-generation antihistamine for allergic rhinitis and urticaria, is widely used in all age groups but lacks appropriate dosing guidelines for pediatric patients, leading to off-label prescriptions. We conducted this study to propose an optimal dosing regimen for pediatric patients based on population pharmacokinetic (popPK) and physiologically based pharmacokinetic (PBPK) models using data from two previous trials. A popPK model was built using NONMEM software. A one-compartment model with first-order absorption and absorption lag time described our data well, with body weight incorporated as the only covariate. A PBPK model was developed using PK-Sim software version 10, and the model well predicted the drug concentrations obtained from pediatric patients. Furthermore, the final PBPK model showed good concordance with the known properties of bepotastine. Appropriate pediatric doses for different weight and age groups were proposed based on the simulations. Discrepancies in recommended doses from the two models were likely due to the incorporation of age-dependent physiological factors in the PBPK model. In conclusion, our study is the first to suggest an optimal oral dosing regimen of bepotastine in pediatric patients using both approaches. This is expected to foster safer and more productive use of the drug.

Capital structure, business model innovation, and firm performance: Evidence from Chinese listed corporate based on system GMM model.

This paper aims to verify the impact of capital structure on business model innovation and firm performance and the mediating effect of business model innovation. We use the data of the Chinese growth enterprises market (GME) listed high-tech firms from 2016 to 2022 as a dynamic panel data model with the system-generalized method of moments (sys-GMM), adopting return on asset and earning per share as firm performance. Our results show that capital structure has a lag effect on firm performance. The total debt ratio in the last period has a significant non-linear impact on the performance and business model innovation level of nowadays, presenting a U-shaped relationship. The first-order lag short-term debt ratio positively improves firm performance. Business model innovation significantly promotes better firm performance, and business model innovation does exist in the mediating effect between enterprise capital structure and its performance. These results remain robust to different sample sizes or proxy variables. This paper proposes some suggestions for firm operations and government policies based on the findings.

Model based assessment of food and acid reducing agent effects on oral absorption of mezigdomide (CC-92480), a novel cereblon E3 ligase modulator.

Mezigdomide is a novel cereblon E3 ligase modulator (CELMoD) agent with enhanced autonomous cell-killing activity in multiple myeloma (MM) cells, and promising immunomodulatory and antitumor activity in patients with MM. We developed a population pharmacokinetics (PKs) model for mezigdomide in healthy subjects (HSs), and quantified effects of high-fat meal and proton pump inhibitor (PPI) on human disposition parameters. Plasma concentrations from 64 HS in two phase I clinical studies (NCT03803644 and NCT04211545) were used to develop a population PK model. The HSs received single oral doses of 0.4-3.2 mg mezigdomide with full PK profiles collected. A two-compartment linear PK model with first-order absorption and lag time best described mezigdomide PK profiles in HSs. The population PK parameters of absorption rate constant, lag time, central volume of distribution, clearance, peripheral volume of distribution, and intercompartmental clearance were estimated to be 1.18 h-1 (interoccasion variability [IOV]: 65%), 0.423 h (IOV: 31%), 440 L (interindividual variability [IIV]: 63%), 35.1 L/h (IIV: 40%), 243 L (IIV: 26%), and 36.8 L/h (IIV: 26%), respectively. High-fat meal increased oral bioavailability by ~30% and PPI co-administration decreased oral bioavailability by ~64%. Mezigdomide demonstrated a linear dose-exposure relationship in HSs. The PK model suggests a modest effect of high-fat meal, and a substantial effect of PPIs on mezigdomide oral bioavailability. This population PK model enables data integration across studies to identify important covariate effects and is being used to guide dose selection in clinical study designs for mezigdomide in patients with MM.

Analysis of HepG2 cell response to a wide concentration range of mitomycin C using a multichannel quartz crystal microbalance system with a microscope

The morphological response of HepG2 cells to mitomycin C was analyzed using a multichannel quartz crystal microbalance system equipped with a home-built movable microscope that enables the simultaneous acquisition of cell images and measurements of eight-channel quartz crystal microbalance. After 24 h of cell seeding, mitomycin C was injected into the culture medium. During the attachment process, the resonant frequency decreased, and the curves fitted well with the first-order lag response. Analysis of the response to mitomycin C revealed that the resonant frequency response curves varied with mitomycin C concentration. When the mitomycin C concentration was <10 μmol L−1, the delay time was observed before the increase in resonant frequency. When the mitomycin C concentration was extremely low, an additional decrease in resonant frequency was observed in the middle of the delay time that fitted well with the cumulative log-normal distribution curve. The resonant frequency response curves after the delay time fitted well with the cumulative log-normal distribution curves. The delay time and mean cumulative log-normal distribution time for the increase in resonant frequency correlated with the mitomycin C concentration; however, the mean time for the additional decrease in the resonant frequency did not show a statistically significant difference as a function of mitomycin C concentration. For mitomycin C concentrations of >20 μmol L−1, the response to the change in resonant frequency was rapid, and the response curves fitted well with the first-order lag response. The first-order lag response indicates that the response occurred simultaneously for all cells. The results showed that the time constant was independent of the tested mitomycin C concentration between 20 and 100 μmol L−1. These results suggested that different cell death processes occurred by mitomycin C. The findings of this study suggest that the system can be used to investigate cell death in adherent cells.

Model Predictive Controller Approach for Automated Vehicle's Path Tracking.

In this paper, a model predictive control (MPC) approach for controlling automated vehicle steering during path tracking is presented. A (linear parameter-varying) LPV vehicle plant model including steering dynamics is proposed to determine the system evolution matrices. The steering dynamics are modeled in two different ways by using first-order lag and a second-order lag; the application of the first-order system resulted in a slightly more accurate path-following. Additionally, a cascade MPC structure is applied in which two MPCs are used; the second-order steering dynamics are separated from the path-following controller in a second MPC. Both steering system models and the cascade MPC are evaluated in simulation and on a test vehicle. The reference trajectory is calculated based on a fixed predefined path by transforming the necessary path segment to the vehicle ego coordinate system, thereby describing the reference for the path-following task in a novel way. The MPC method computes the optimal steering angle vector at each time step for following the path. The longitudinal dynamics is controlled separately by a PI controller. After simulation evaluation, experimental tests were conducted on a test vehicle on an asphalt surface. Both simulation and experimental results prove the effectiveness of the proposed reference definition method. The effect of the applied steering system models is evaluated. The inclusion of the steering dynamics in the prediction model resulted in a significant increase in controller performance. Finally, the computational requirements of the proposed control and modeling methods are also discussed.

Monitoring process stability in gas metal arc additive manufacturing based on arc sensing

Gas metal arc additive manufacturing (GMA AM) is a promising technology for fabricating large-size metal parts. Nevertheless, process monitoring to achieve repeatable and reliable depositions is yet to be completely realized. This study aims to monitor the process stability, i.e., nozzle to top layer distance (NTLD), in GMA AM based on arc sensing. Relationships between arc signals and the NTLD in three droplet transfer modes are studied and discussed, and four filtering algorithms are applied to remove noises in arc signals. The arc current is superior to the arc voltage to characterize the deposition height and is most sensitive to the NTLD in the globular transfer mode. The adaptive least mean square method can eliminate noises in arc current more effectively than the median average, first-order lag, and Kalman algorithms. Validation tests indicate that the arc current sensing can detect the NTLD in GMA AM.

The impact of pandemic mental cognition on cultural values: an empirical study based on social media

BackgroundCOVID-19 has triggered a global public health crisis, and had an impact on economies, societies, and politics around the world. Based on the pathogen prevalence hypothesis suggested that residents of areas with higher infection rates are more likely to be collectivists as compared with those of areas with lower infection rates. Many researchers had studied the direct link between infectious diseases and individualism/collectivism (infectious diseases→ cultural values), but no one has focused on the specific psychological factors between them: (infectious diseases→ cognition of the pandemic→ cultural values). To test and develop the pathogen prevalence hypothesis, we introduced pandemic mental cognition and conducted an empirical study on social media (Chinese Sina Weibo), hoping to explore the psychological reasons behind in cultural value changes in the context of a pandemic.MethodsWe downloaded all posts from active Sina Weibo users in Dalian during the pandemic period (January 2020 to May 2022) and used dictionary-based approaches to calculate frequency of words from two domains (pandemic mental cognition and collectivism/individualism), respectively. Then we used the multiple log-linear regression analysis method to establish the relationship between pandemic mental cognition and collectivism/individualism.ResultsAmong three dimensions of pandemic mental cognition, only the sense of uncertainty had a significant positive relationship with collectivism, and also had a marginal significant positive relationship with individualism. There was a significant positive correlation between the first-order lag term AR(1) and individualism, which means the individualism tendency was mainly affected by its previous level.ConclusionsThe study found that more collectivist regions are associated with a higher pathogen burden, and recognized the sense of uncertainty as its underlying cause. Results of this study validated and further developed the pathogen stress hypothesis in the context of the COVID-19 pandemic.

Research and design of an intelligent fish tank system.

In order to improve the hardware configuration and interaction mode of the fish tank system and realize the diversification of client functions, the purpose of real-time remote monitoring and management is achieved. A set of IoT intelligent fish tank system composed of sensor unit, signal processing unit and wireless transmission unit was designed. The system improves the algorithm of the data collected by the sensor, and proposes an improved first-order lag average filtering algorithm. The system uses composite collection information, intelligent processing, chart data analysis and other methods to transmit the processed data to the cloud server through the WIFI communication module. An APP is designed on the remote monitoring and control end, and a visual data interface of the smart fish tank is made, and the user can modify the environmental parameters conducive to the biological survival inside the fish tank through the APP, it brings great convenience to the family fish tank, and the test shows that the system network is stable and fast in response, and the overall purpose of the intelligent fish tank system is achieved.

A Dual Aircraft Maneuver Formation Controller for MAV/UAV Based on the Hybrid Intelligent Agent

This paper proposes a hybrid intelligent agent controller (HIAC) for manned aerial vehicles (MAV)/unmanned aerial vehicles (UAV) formation under the leader–follower control strategy. Based on the high-fidelity three-degrees-of-freedom (DOF) dynamic model of UAV, this method decoupled multiple-input-multiple-output (MIMO) systems into multiple single-input-single-output (SISO) systems. Then, it innovatively combined the deep deterministic policy gradient (DDPG) and the double deep Q network (DDQN) to construct a hybrid reinforcement learning-agent model, which was used to generate onboard desired state commands. Finally, we adopted the dynamic inversion control law and the first-order lag filter to improve the actual flight-control process. Under the working conditions of a continuous S-shaped large overload maneuver for the MAV, the simulations verified that the UAV can achieve accurate tracking for the complex trajectory of the MAV. Compared with the traditional linear quadratic regulator (LQR) and DDPG, the HIAC has better control efficiency and precision.

Steering Potential for Printing Highly Aligned Discontinuous Fibre Composite Filament.

DcAFF (discontinuous aligned fibre filament) is a novel material for fused filament fabrication (FFF) 3D printing made of highly aligned discontinuous fibres produced using high performance discontinuous fibre (HiPerDiF) technology. It reinforces a thermoplastic matrix to provide high mechanical performance and formability. Accurate printing of DcAFF poses a challenge, especially for complex geometries, because: (i) there is a discrepancy between the path where the filament experiences the adhering pressure from the filleted nozzle and the nozzle path; and (ii) the rasters display poor adhesion to the build platform immediately after deposition, which causes the filament to be dragged when the printing direction changes. This paper explains the implication of these phenomena on steering capabilities and examines the techniques for improving DcAFF printing accuracy. In the first approach, the machine parameters were adjusted to improve the quality of the sharp turning angle without changing the desired path, but this showed insignificant effects in terms of precision improvements. In the second approach, a printing path modification with a compensation algorithm was introduced. The nature of the inaccuracy of the printing at the turning point was studied with a first-order lag relationship. Then the equation to describe the deposition raster inaccuracy was determined. A proportional-integral (PI) controller was added to the equation to calculate the nozzle movement in order to bring the raster back to the desired path. The applied compensation path is shown to give an accuracy improvement in curvilinear printing paths. This is particularly beneficial when printing larger circular diameter curvilinear printed parts. The developed printing approach can be applied with other fibre reinforced filaments to achieve complex geometries.

Design and Comparative Analysis of Several Model Predictive Control Strategies for Autonomous Vehicle Approaching a Traffic Light Crossing

Recent advancements in automated driving technology and vehicle connectivity are associated with the development of advanced predictive control systems for improved performance, energy efficiency, safety, and comfort. This paper designs and compares different linear and nonlinear model predictive control strategies for a typical scenario of urban driving, in which the vehicle is approaching a traffic light crossing. In the linear model predictive control (MPC) case, the vehicle acceleration is optimized at every time instant on a prediction horizon to minimize the root-mean-square error of velocity tracking and RMS acceleration as a comfort metric, thus resulting in a quadratic program (QP). To tackle the vehicle-distance-related traffic light constraint, a linear time-varying MPC approach is used. The nonlinear MPC formulation is based on the first-order lag description of the vehicle velocity profile on the prediction horizon, where only two parameters are optimized: the time constant and the target velocity. To improve the computational efficiency of the nonlinear MPC formulation, multiple linear MPCs, i.e., a parallel MPC, are designed for different fixed-lag time constants, which can efficiently be solved by fast QP solvers. The performance of the three MPC approaches is compared in terms of vehicle velocity tracking error, root-mean-square acceleration, traveled distance, and computational time. The proposed control systems can readily be implemented in future automated driving systems, as well as within advanced driver assist systems such as adaptive cruise control or automated emergency braking systems.

Thickener as an automatic control object

Introduction. Grain motion in the process of pulp sedimentation in a radial thickener was studied to use the typical links of the automatic control system. Research objective is to explore the possibility of describing the sedimentation process by means of typical links of the automatic control theory based on the physics of grain motion in a radial thickener and the equation of grain motion under laminar and turbulent flow conditions. Methods of research. Stokes’ law that determines the drag force resisting a solid sphere when it slowly moves forward in an unbounded viscous fluid (laminar motion) and the Newton– Rittinger law for the turbulent motion of grain formed the basis of the mathematical model, making it possible to develop a program that chooses a particular equation to calculate the grain sedimentation time in accordance with the grain size. The equations helped to obtain the sedimentation time and hence the time taken to reach the thickener’s bottom, which, in their turn, together with the fractional composition, determine the performance of the thickener. Transition curves were thereby obtained for various granulometric composition, percentage of ore in the pulp, thickener height, ore and pulp density. In the future, this made it possible to approximate the process of sediment accumulation by the equations of one or two lag blocks of the automatic control system. Research results. A computer program has been used that describes the process of sediment accumulation in a thickener, considering the granulometric composition as well as pulp and ore grain density. The program showed that the process of sediment accumulation in a thickener can be described with fair accuracy by a first-order lag block for laminar or turbulent grain motion. For a mixture of coarse and fine fractions, ore sedimentation can be approximated by two parallel lag blocks. Conclusions. Sedimentation process approximation by lag blocks, obtained with fair accuracy, can be used when analyzing, designing and adjusting sedimentation automatic control systems.

Determinants of Barley Output Supply Response in Ethiopia: Application of Ardl Bound Cointegration Approach

This study investigated barley output supply response determinant factors in Ethiopia. An ARDL bound test approach was employed as method using secondary data from 1981-2020. The study demonstrated that barley output supply was affected positively and significantly by zero-order lagged seasonal rainfall and crop growing period temperature. The study supports the findings of researchers who reported that warming temperature followed by an increase in the amount of rainfall had a positive impact on barley output supply. The positive impact of temperature was induced because of a rise in the ocean and earth’s surface average temperature, causing more evaporation that increases overall rainfall while reaching over the highland areas. Studies confirm that ENSO and moist winds coming from the Atlantic and Indian Oceans influence the occurrence of rainfall in the western, southeastern, central, and northern highlands of Ethiopia. The study further exhibited that CSMRR and CGPMT had a positive effect on barley output both in the long-run and short-run, implying that climate parameters have minimal effect on barley production. Nonclimatic variables demonstrated that both lagged and current year’s producer prices had a positively significant effect on barley output supply in both the long-run and short-run, implying that barley output supply is highly responsive to any price incentive strategies announced before re-allocation of the area towards barley cultivation. Conversely, the study explored that use of fertilizer in first-order lag had negatively significant impact on barley output supply in both seasons; implying that increased use of fertilizer in lagged period may reduce barley output as a result of inappropriate fertilizers application by farmers. The results generated by this study are useful addendum to the repository of knowledge on elasticity of crop supply at an aggregate level, which can be used in designing strategies and measures for mitigation and adaptation of climate change.

Technological progress for sustainable development: An empirical analysis from China

Sustainable development has become a new engine to promote economic growth, in which scientific and technological progress, green finance and the efficient development of a green economy have become the main driving forces of economic and societal development. Hence, the continuous improvement of innovation ability through scientific research innovation, as well as the rapid development of the technology market, is an important force for the sustainable development of China. Therefore, by first analysing the related data from 2001 to 2020 of China’s technology market, the time series value of the comprehensive evaluation is obtained. Then, based on the unit root test, cointegration test and Granger causality, this study explores the relationship between the technology market turnover and scientific research innovation. The results show a second-order cointegration between the technology market turnover and scientific research innovation. Scientific research innovation can promote the development of the technology market from the perspective of long-term equilibrium and reverse correction in the short term. Mutual Granger causality and a first-order significant lag are observed between technology market development and scientific research innovation. It is necessary to further improve the management mechanism of the technology market. The government should promote the continuous innovative development of the technology market to improve the efficiency of resource allocation and enhance the connection between the technology market and innovation subjects.